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Bortolon, Alessandro

Publications and source records attributed to Bortolon, Alessandro.

14 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Tungsten erosion and divertor leakage from the DIII-D SAS-VW tungsten-coated divertor in experiments with neon gas seeding

Collector probes have been used to examine tungsten divertor leakage in a variety of scenarios with low-Z impurity seeding during operation with the new tungsten-coated SAS-VW divertor in DIII-D. Measurements of tungsten deposition on collector probes inserted into the far Scrape-off-Layer (SOL) are used to deduce how efficiently tungsten leaks out of the closed, V-shaped divertor after it is eroded from the target surfaces. Qualitative differences in the tungsten deposition patterns across the collector probes provide clear experimental evidence that the SOL conditions depend on the low-Z impurity seeding conditions. These measurements show that in scenarios where neon gas is injected into the plasma, the tungsten divertor leakage and SOL transport depend on the poloidal location from which the neon is injected. In particular, neon injection from the Inner Midplane and Outer Midplane appear to each result in higher divertor leakage by a factor of 2 to 3 compared to cases with neon injection from either the SOL Crown or from the SAS-VW divertor itself.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Design of a Novel Variable Geometry Divertor for Tokamaks

The divertor is a key component of fusion reactors, allowing exhaust of gas, impurities, and helium ash to preserve plasma purity. The divertor geometry strongly affects plasma performance, and it is designed to be compatible with different plasma shapes in present-day fusion experiments. Here, we present a novel concept for a variable geometry divertor, in which the divertor baffle tiles are reorientable by external actuation. Implementation of this concept in a medium-sized research tokamak would uniquely provide the flexibility to tailor divertor geometry to the plasma configuration and also enable study of the effect of divertor closure on plasma performance. To ensure compatibility with typical tokamak operations, the adjustable divertor must withstand the effects of significant mechanical and thermal stresses such as MW/m 2 -scale heat fluxes and large electromagnetic fields, e.g., disruption forces. The technological solutions for actuation mechanisms, cooling system, gas baffling and plasma-facing components are assessed. A functional reduced-scale model with movable outer divertor target baffle tiles is developed and the actuation mechanism is tested.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Initial results from boron powder injection experiments in WEST lower single null L-mode plasmas

Using a recently installed impurity powder dropper (IPD), boron powder (<150 μm) was injected into lower single null (LSN) L-mode discharges in WEST. IPDs possibly enable real-time wall conditioning of the plasma-facing components and may help to facilitate H-mode access in the full-tungsten environment of WEST. The discharges in this experiment featured I p = 0.5 MA, B T = 3.7 T, q 95 = 4.3, t pulse = 12–30 s, n e,0 ~ 4 × 10 19 m –2 , and P LHCD ~ 4.5 MW. Estimates of the deuterium and impurity particle fluxes, derived from a combination of visible spectroscopy measurements and their corresponding S/XB coefficients, showed decreases of ~50% in O + , N + , and C + populations during powder injection and a moderate reduction of these low-Z impurities (~50%) and W (~10%) in the discharges that followed powder injection. Along with the improved wall conditions, WEST discharges with B powder injection observed improved confinement, as the stored energy W MHD , neutron rate, and electron temperature T e increased significantly (10%–25% for W MHD and 60%–200% for the neutron rate) at constant input power. Notably, these increases in confinement scale up with the powder drop rate and are likely due to the suppression of ion temperature gradient (ITG) turbulence from changes in Z eff and/or modifications to the electron density profile.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Prediction of DIII-D Pedestal Structure from Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. An experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (ne) and electron temperature (Te) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (Ip), toroidal magnetic field (Bφ), neutral beam heating power (PNBI) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Initial Results from Boron Powder Injection Experiments in WEST Lower Single Null L-mode Plasmas

Using a recently installed impurity powder dropper (IPD), boron powder (< 150 μm) was injected into lower single null (LSN) L-mode discharges in WEST. IPDs possibly enable real-time wall conditioning of the plasma-facing components and may help to facilitate H-mode access in the full-tungsten environment of WEST. The discharges in this experiment featured Ip = 0.5 MA, BT = 3.7 T, q95 = 4.3, tpulse = 12–30 s, ne,0 ~ 4×1019 m-2, and PLHCD ~ 4.5 MW. Estimates of the deuterium and impurity particle fluxes, derived from a combination of visible spectroscopy measurements and their corresponding S/XB coefficients, showed decreases of ~ 50% in O+, N+, and C+ populations during powder injection and a moderate reduction of these low-Z impurities (~ 50%) and W (~ 10%) in the discharges that followed powder injection. Along with the improved wall conditions, WEST discharges with B powder injection observed improved confinement, as the stored energy WMHD, neutron rate, and electron temperature Te increased significantly (10–25% for WMHD and 60–200% for the neutron rate) at constant input power. These increases in confinement scale up with the powder drop rate and are likely due to the suppression of ion temperature gradient (ITG) turbulence from changes in Zeff and/or modifications to the electron density profile.

Boronization↗
DOE OSTI2021

Pellet triggering of edge localized modes in low collisionality pedestals at DIII-D

Edge localized modes (ELMs) are triggered using deuterium pellets injected into plasmas with ITER-relevant low collisionality pedestals, and the resulting peak ELM energy fluence is reduced by approximately 25%–50% relative to natural ELMs destabilized at similar pedestal pressures. Cryogenically frozen deuterium pellets are injected from the low-field side of the DIII-D tokamak at frequencies lower than the natural ELM frequency, and heat flux is measured by infrared cameras. Ideal MHD pedestal stability calculations show that without pellet injection, these low collisionality pedestals were limited by their current density (peeling-limited) rather than their pressure gradient (ballooning-limited). ELM triggering success correlates strongly with pellet mass, consistent with the theory that a large pressure perturbation is required to trigger an ELM in low collisionality discharges that are far from the ballooning stability boundary. For sufficiently large pellets, both instantaneous and time-integrated ELM energy deposition measured by infrared cameras is reduced with respect to naturally occurring ELMs at the inner strike point, which is the position where it is largest for natural ELMs. Energy fluence at the outer strike point is less effected. Cameras observing both heat flux and D-alpha emission often find significant toroidally asymmetric striations in the outboard far scrape-off layer resulting from ELMs that are triggered by pellets. Toroidal asymmetries at the inner strike point are similar between natural and pellet-triggered ELMs, indicating that the reduction in peak heat flux and total fluence at that location is robust for the conditions reported here.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Prediction of DIII-D Pedestal Structure From Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. Here, an experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (n e ) and electron temperature (T e ) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (I p ), toroidal magnetic field (B Φ ), neutral beam heating power (P NBI ) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Full-orbit simulations of fast-ion charge-exchange losses induced by neutral particles outside the plasma last closed flux surface

The interaction between neutrals outside tokamak plasmas and fast ions that are generated by neutral beam injection and pass outside the plasma is studied. It is shown that at beam energies (up to ~100~keV) fast-ion losses are significant, up to 20% in the studied case, because of charge exchange reactions between the neutrals and the fast ions. About half of the fast ions that neutralize outside the plasma get lost to the wall while the other half re-enter the plasma and ionize again, often on better confined orbits which is visible as an enhanced beam power deposition in the plasma core (rho ~< 0.7). As a result, the the plasma performance as measured from the beam-thermal neutrons is hardly changed despite the significant fast-ion losses toward the plasma edge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗